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Uniting and Standardizing Healthcare Provision Across
Dubai
Session 138, February 13 2018
Associate Professor Jane Griffiths Chief Nursing Informatics Officer, Dubai
Health Authority
Qasim Abuhantash Senior Specialist, Dubai Health Authority
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Associate Professor Jane Griffiths RN, BAN, MHP
Qasim Yousef Qasim Abuhantash BS, MA
Have no real or apparent conflicts of interest to report.
Conflict of Interest
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Learning Objectives
Purpose
Outline
Background
Environment of DHA
Strategic Direction
Methodology
Improvements and Optimisation
Innovation
Case Studies
Sepsis
Suicide Assessment
Challenges
Outcomes
Conclusion
References
Agenda
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Discuss the benefits of an electronic medical record in providing
innovative care
Assess how the international evidence is used as the basis for the
changes in clinical practice and culture across healthcare
Demonstrate how DHA will guide the EMR agenda for the Emirate
of Dubai and the region
Learning Objectives
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His Highness Sheikh Mohammed bin Rashid Al Maktoum, Vice
President and Prime Minister of the UAE and Ruler of Dubai
called on all Dubai Government entities to embrace disruptive
innovation as a fundamental mantra of their operations and to
seek ways to incorporate its methodologies in all aspects of their
work.
Each Government Department was to seek ways to incorporate
these methodologies in all aspects of their work
Purpose
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To comply with Sheikh Mohammed’s directive the Dubai Health
Authority (DHA) contracted a USA based vendor to implement an
EMR across all government health facilities in 2015.
At the same time, the governing Board of Directors issued a
requirement that standardization of clinical practice based on
international evidence was to be implemented across all facilities
in DHA.
The decision was made to utilize the implementation of the EMR
to facilitate the standardization of work practices across DHA and
to provide the platform for sustainable, efficient and effective
health care of the future.
Outline
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The EMR selected was named “Salama” (means safety in Arabic)
Not only is it essential to engage end users in the implementation
of the EMR, it is imperative to engage these end-users with the
clinical standardization process
Our end users understand how our health facilities work & were
already frustrated with processes that were duplicated or not
effective
Background
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This engagement technique ensured staff took responsibility for
their own work practices rather than using excuses such as:
It is a decree from higher management
It’s policy
Background
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23 applications in the Enterprise system were implemented
including a patient portal
Salama successfully went live in 2017
128 million existing records were migrated to the new EMR
2018 has seen the optimization phase for the implementation of
new initiatives
Since then additional technology has been implemented
Background
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12,000 staff are employed in DHA
Full range of different disciplines, education levels & cultures
4 hospitals
12 Primary Health Care Centres
10 free standing Specialty Centres
18 Medical Fitness Centres
5 Occupational Health Centres
1 Nursing Home
Environment of DHA
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Strategic Direction
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Strategic Direction
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The quality and safety literature identifies that 60% of our work
does not add value to the patient’s experience.
The purpose of an EMR is to streamline services and provide
unprecedented access to information.
DHA made the choice to use lean methodology during the
implementation phase of the EMR to ensure:
Standardization (clinical policies)
Elimination of waste (reduced duplication of data entry)
Cost effective care (ensuring appropriate charges applied)
Increase patient safety (closed loop medication
administration)
Improve patient satisfaction (patient education provided in
Arabic)
Methodology
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Over 500 staff were actively involved in the standardization
process
This technique ensured staff took responsibility for their own work
practices
Final agreements for changes in work practices were based on
international references & best practices
Over 500 workflows were revised & 150 policies reviewed
Compliance and sustainability is reviewed daily/monthly
Bar code scanning of patients and medication administration
went from 78% to 99% and has been sustained since 2017
Methodology
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Improvements or changes to the system use a process whereby
endusers log a “jira” ticket to the Salama Help Desk
This ticket is allocated to the relevant application build team &
provided a prioritization code (benchmark time to resolve)
They review the request to ensure the end-user is maximizing the
use of Salama or whether to achieve the change, the system has
to be modified
If a change is identified then a change request is taken for review
to the relevant Governance Council (PAC, NAC, QAC, FAC,
PTAC)
The Councils consist of senior clinical & admin staff who have
delegated authority from all facilities to authorize a change in the
build
Improvements & Optimisation
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In 12 months
27,027 Jira tickets have been raised
26,838 tickets have been resolved
In addition 81 optimization changes have been built &
implemented
89 tip/design sheets for end-users have been developed &
implemented
2,502 reports have been built
2.1 million pts are covered in the integrated, effective EMR
implemented across DHA
Improvements & Optimisation
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Salama is integrated with other Dubai Government Departments
including:
Dubai Police
Dubai Ambulance Service
Al Jalila Children’s Hospital
Directorate of Residency & Foreign Affairs
Licensing & Regulation
Dubai Smart Government
Innovations
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Additional technology
Artificial Intelligence
TB diagnosis
Retinal scanning
Septic shock
Deteriorating pts
Innovations
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Robotics
Medications
Hand Held Devices
Closed loop barcoding medication administration
Blockchain materials management
Innovations
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Patient by default of a high risk of fall.
Neonates & Infants
OT & PACU Patients
ICU including NICU patients
Patients in the Resuscitation area of the Emergency Department
Case Study - Falls Assessment
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Verbal orders emergency situation with physician present
Telephone orders physician outside the facility
Delete telephone orders from the system
Case Study Telephone Orders
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Screening Tool
The first level is sadness and depression levels (example of
questions that explore this level will be: How you feel, tell me
about your feeling, for the past two days did you notice change in
your feeling affected your appetite to eat, sleep, socialize..)
The second level cover the concept of ”wish to die” (example of
questions will be: based on the positive answer in the first level,
this sad feeling make you feel that life is nothing living? Wishing to
sleep and not wake up, living is painful..
The third level asking about suicidal attempts (example of
questions would be: based on the above did you tried or thought
to harm yourself…tried to kill yourself and if yes what you used…
All hospitals should have action plan for the third level as per the
suicidal policy
Case Study Suicide Assessment
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Validation of the tool undertaken 30 times across all hospitals,
covered different types of patients
Nationality (Arab, Indian, Filipino, ..)
Gender (male, female)
Age (adult, adolescents)
There is general acceptance from the patients to answer and to
talk about the topics been discussed
Some patients showed more interests to talk further about their
emotional and psychological status (patients said “nobody before
talk or care about our feelings…”)
Case Study Suicide Assessment
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Case Study Sepsis
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The aim is to develop an early detection system to help identify
when an inpatient’s condition will deteriorate in the future and
allow treatment/monitoring to be implemented before the
deterioration occurs.:
Date range : 1-Dec-17 to 30-Nov-18
Vitals data : MRN, Encounter No, Admitted time, Discharge
Time, Flowsheet name (vital signs), Reading Date/Time,
Reading Department and Specialty, Duration of Stay,
Timestamp.
Demographic data : MRN, Encounter No, Age, Gender,
Weight, Height, and BMI.
Response times for intervention.
Any procedures undertaken.
Transfer out of ICU
AI Deteriorating Patients
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5921 patient encounters with 369,067 observations (average of
61 observations per encounter) were used
The overall accuracy of the system is 89.91%.
Risk Threshold of 0.4.
The model needs at least 3 historical data points
The model can predict if the patient’s health will deteriorate within
5 future time periods.
17.5% of all patients identified at risk of
deteriorating and who subsequently did
deteriorate were transfers out of ICU
AI Deteriorating Patients
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3 previous attempts to implement an EMR had been started in
DHA
Staff were initially cynical if this implementation would proceed &
therefore were reluctant to become engaged
Clinical & admin practices were not standardized across DHA &
endusers all believe their own practice was “the best”
Training & “go live” support were managed differently in each
facility
Competition between facilities (both a challenge & an advantage)
Challenges
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Implementation was undertaken in 3 phases
All sites/facilities went live within 7 months
Successful implementation was validated by the achievement of
EMRAN & O-EMRAN Stage 6 within 8 weeks of “go live” in:
4 hospitals
All PHCs
All Specialty Centres
Adoption and sustainability are measured daily/weekly/monthly
through reports/dashboards for individual clinicians and higher
management
Outcomes
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To achieve cross facility standardization required input from all
facilities & staff
In order to reduce waste in the system, we reviewed our current
processes & implemented standardized evidence based
workflows & practices across DHA
The review identified current inefficiencies & mistakes which were
removed/changed
This allowed a fully integrated, effective EMR to be implemented
across DHA
Conclusion
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Ackerman ,J. Hemphill , R., Cowan, D (2011) Lean Is a Tool in the Toolbox, Not the Silver Bullet. Annals of
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Atkinson P, Mukaetova-Ladinska EB. (2012) Nurse-led liaison mental health service for older adults: service
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http://www.ncbi.nlm.nih.gov/pubmed/22405230
Grove , A., Meredith J, Macintyre M, Angelis J, Neailey, K (2010) Lean implementation in primary care
health visiting services in National Health Service UK Qual Saf Health Care doi:10.1136/qshc.2009.039719
http://qualitysafety.bmj.com/content/early/2010/05/28/qshc.2009.039719.full.html
Holder, R . (2011) Lean Thinking in emergency departments: a critical review. Annals of Emergency
Medicine 57(3):265-78. doi:10.1016/j.annemergmed.2010.08.001.
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Kollberg, B., Dahlgaard, J.J., Brehmer, P-O. (2007). Measuring lean initiatives in healthcare services: issues
and findings. International Journal of Productivity and Performance Management, 56(1), 7-24.
http://www.emeraldinsight.com/journals.htm?articleid=1585212&show=html
Judith Wuest, Marilyn Merritt-Gray, Norma Dube´, Marilyn J. Hodgins, Jeannie Malcolm, Jo Ann Majerovich,
Kelly Scott-Storey, Marilyn Ford-Gilboe, Colleen Varcoe (2015) The Process, Outcomes, and Challenges of
Feasibility Studies Conducted in Partnership With Stakeholders: A Health Intervention for Women Survivors
of Intimate Partner Violence. 82-96 https://onlinelibrary.wiley.com/doi/pdf/10.1002/nur.21636
References
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Contacts
Associate Professor Jane Griffiths jlgriffiths@dha.gov.ae
Qasim Yousef Qasim Abuhantash Qasimya@dha.gov.ae
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